WRF/UCM Simulations of Urban Heat Island in Guangzhou with an Extracted Land-use Map from the Remote Sensing Data

Abstract: In order to
investigate the performance of weather research and forecasting (WRF) model coupled
with an urban canopy model (UCM) with an extracted land use data from Remote
Sensing data(RS), three numerical experiments with different geographic models
were carried out. Supervisedclassification with the maximum likelihood was
applied to extract the land-use map in Guangzhou 2012named the geographic model
RS_12. Then based on the satellite-measured night time light data and thenormalized
difference vegetation index, a human settlement index was used to classify the
urban land category to three urban land subcategories in the UCM as another
geographic model named UCM_12. Both new geographic model simulation results are
capable of reasonably modeling the observation result. The UCM_12 reasonably
reproduced the best 2-m temperature evolution and the minimum root-mean- - square-error
as compared with other experiments. Experiments with new geographic models can
capture the strongest UHI time occured at night and gradually decreases in the
morning but failure to get negativeat noon. A better accuracy when comparing
the new geographic models to the observation proved that extract land use data
from RS can be used in urban scale simulation under the fast urbanizition in
China.